| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Skellefteå AIK U20 | SHL-J20 | 36 | 2 | 12 | 14 | 0.389 | 0.2148 | 0.2206 | 0.5191 | 0.5330 |
| 2023-24 | — | BCHL | 42 | 6 | 16 | 22 | 0.524 | 0.2018 | 0.2035 | 0.7632 | 0.7697 |
| 2024-25 | Corpus Christi IceRays | NAHL | 55 | 9 | 32 | 41 | 0.746 | 0.2648 | 0.2583 | 0.7827 | 0.7636 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Lake Superior State | D1 | CCHA | — | 5 | 0 | 0 | 0 | 0.000 |
How to read this: NCAAe and D3e factors convert a player's junior PPG into expected NCAA scoring at the D1 or D3 level. Harder conferences → lower projected PPG for the same player. A strong junior player (e.g. USHL 0.90 PPG) will project much higher in NESCAC than Big Ten because the D3 scoring environment is lower-difficulty.
Strength factor: conferences above 1.0 are harder than average; below 1.0 are easier. The formula is: Base NCAAe PPG ÷ Conference Strength = Projected PPG.